Senior Data Scientist I

🕒 April 23

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Advarra

501 - 1000 employees

Founded 1983

🏥 Healthcare

💼 Consulting

☁️ SaaS

Healthcare • Consulting • SaaS

Advarra is a provider of integrated regulatory oversight and clinical trial technology, combining independent IRB review and compliance services with enterprise SaaS platforms (including Braid, OnCore, Clinical Conductor, eReg, and eSource). The company delivers operational intelligence, AI-powered protocol design and automation, site collaboration, study startup and enrollment tools, and strategic enablement services to sponsors, CROs, research sites, and institutions to improve efficiency, compliance, and patient safety across the clinical trial lifecycle.

📋 Description

• Focus on understanding existing models, assessing their performance, selecting optimal architectures, and fine-tuning them to meet specific domain and business needs • Collaborate closely with data engineering, product, and domain teams to translate real-world research challenges into scalable, model-driven solutions • Optimize and fine-tune large language models (LLMs) and domain-specific variants using proprietary datasets • Evaluate model performance across key metrics and benchmarks • Implement and operationalize LLM-based and retrieval-augmented (RAG) systems • Collaborate with data engineering to ensure scalable, efficient model training, evaluation, and deployment pipelines • Assess and select models that best align with domain-specific requirements and Advarra’s regulated research environment • Partner with clinical and operational experts to translate research and trial challenges into measurable model evaluation frameworks • Conduct model interpretability and bias analyses • Document methodologies and validation results

🎯 Requirements

• MS in Machine Learning, Computer Science, or related quantitative discipline, or equivalent relevant work experience • 5+ years of hands-on experience developing and fine-tuning ML or LLM models • Demonstrated expertise in Python, with experience and knowledge of a commercial framework like PyTorch • Hands-on experience developing, managing, and troubleshooting workflows within Databricks for data engineering, analytics, and machine learning projects • Documented strong understanding of the ML lifecycle • Experience with embeddings and retrieval-augmented generation (RAG)

🏖️ Benefits

• Health coverage • Paid holidays • Variable bonus

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